Personals scripts using ageitgey/face_recognition

Overview

HOW TO USE

  1. pip3 install requirements.txt
  2. Add some pictures of known people in the folder 'people' : a) Create a folder called by the name of the person b) Add pictures of it
  3. Add some pictures of unknown people in the uk folder
  4. python3 face_recoginiton.py

OPTIONS

--known_people_folder : Insert custom known_people_folder.

--unknown_people_folder : Insert custom unknown_people_folder.

--cpus : Number of CPU cores to use in parallel (can speed up processing lots of images). -1 means "use all in system".

--tolerance : Tolerance for face comparisons. Default is 0.6. Lower this if you get multiple matches for the same person.

--show-distance : Output face distance. Useful for tweaking tolerance setting.

--show-final : Show best result of recogintion. Use it to get an indicator of the accuracy of the results (lower is better).

Script by @antoinebollengier and principally from https://github.com/ageitgey/face_recognition

Owner
Antoine Bollengier
Antoine Bollengier
This was initially the repo for the project of [email protected] of Asaf Mazar, Millad Kassaie and Georgios Chochlakis named "Powered by the Will? Exploring Lay Theories of Behavior Change through Social Media"

Subreddit Analysis This repo includes tools for Subreddit analysis, originally developed for our class project of PSYC 626 in USC, titled "Powered by

Georgios Chochlakis 1 Dec 17, 2021
Exact Pareto Optimal solutions for preference based Multi-Objective Optimization

Exact Pareto Optimal solutions for preference based Multi-Objective Optimization

Debabrata Mahapatra 40 Dec 24, 2022
Prevent `CUDA error: out of memory` in just 1 line of code.

🐨 Koila Koila solves CUDA error: out of memory error painlessly. Fix it with just one line of code, and forget it. 🚀 Features 🙅 Prevents CUDA error

RenChu Wang 1.7k Jan 02, 2023
PyTorch implementation of SwAV (Swapping Assignments between Views)

Unsupervised Learning of Visual Features by Contrasting Cluster Assignments This code provides a PyTorch implementation and pretrained models for SwAV

Meta Research 1.7k Jan 04, 2023
A PyTorch implementation of Sharpness-Aware Minimization for Efficiently Improving Generalization

sam.pytorch A PyTorch implementation of Sharpness-Aware Minimization for Efficiently Improving Generalization ( Foret+2020) Paper, Official implementa

Ryuichiro Hataya 102 Dec 28, 2022
Implementation of fast algorithms for Maximum Spanning Tree (MST) parsing that includes fast ArcMax+Reweighting+Tarjan algorithm for single-root dependency parsing.

Fast MST Algorithm Implementation of fast algorithms for (Maximum Spanning Tree) MST parsing that includes fast ArcMax+Reweighting+Tarjan algorithm fo

Miloš Stanojević 11 Oct 14, 2022
The software associated with a paper accepted at EMNLP 2021 titled "Open Knowledge Graphs Canonicalization using Variational Autoencoders".

Open-KG-canonicalization The software associated with a paper accepted at EMNLP 2021 titled "Open Knowledge Graphs Canonicalization using Variational

International Business Machines 13 Nov 11, 2022
How Do Adam and Training Strategies Help BNNs Optimization? In ICML 2021.

AdamBNN This is the pytorch implementation of our paper "How Do Adam and Training Strategies Help BNNs Optimization?", published in ICML 2021. In this

Zechun Liu 47 Sep 20, 2022
Deep metric learning methods implemented in Chainer

Deep Metric Learning Implementation of several methods for deep metric learning in Chainer v4.2.0. Proxy-NCA: No Fuss Distance Metric Learning using P

ronekko 156 Nov 28, 2022
Official repository for Hierarchical Opacity Propagation for Image Matting

HOP-Matting Official repository for Hierarchical Opacity Propagation for Image Matting 🚧 🚧 🚧 Under Construction 🚧 🚧 🚧 🚧 🚧 🚧   Coming Soon   

Li Yaoyi 54 Dec 30, 2021
Codes for NAACL 2021 Paper "Unsupervised Multi-hop Question Answering by Question Generation"

Unsupervised-Multi-hop-QA This repository contains code and models for the paper: Unsupervised Multi-hop Question Answering by Question Generation (NA

Liangming Pan 70 Nov 27, 2022
Performance Analysis of Multi-user NOMA Wireless-Powered mMTC Networks: A Stochastic Geometry Approach

Performance Analysis of Multi-user NOMA Wireless-Powered mMTC Networks: A Stochastic Geometry Approach Thanh Luan Nguyen, Tri Nhu Do, Georges Kaddoum

Thanh Luan Nguyen 2 Oct 10, 2022
Group R-CNN for Point-based Weakly Semi-supervised Object Detection (CVPR2022)

Group R-CNN for Point-based Weakly Semi-supervised Object Detection (CVPR2022) By Shilong Zhang*, Zhuoran Yu*, Liyang Liu*, Xinjiang Wang, Aojun Zhou,

Shilong Zhang 129 Dec 24, 2022
Pytorch ImageNet1k Loader with Bounding Boxes.

ImageNet 1K Bounding Boxes For some experiments, you might wanna pass only the background of imagenet images vs passing only the foreground. Here, I'v

Amin Ghiasi 11 Oct 15, 2022
Easy and comprehensive assessment of predictive power, with support for neuroimaging features

Documentation: https://raamana.github.io/neuropredict/ News As of v0.6, neuropredict now supports regression applications i.e. predicting continuous t

Pradeep Reddy Raamana 93 Nov 29, 2022
A large-scale face dataset for face parsing, recognition, generation and editing.

CelebAMask-HQ [Paper] [Demo] CelebAMask-HQ is a large-scale face image dataset that has 30,000 high-resolution face images selected from the CelebA da

switchnorm 1.7k Dec 26, 2022
Implementation of experiments in the paper Clockwork Variational Autoencoders (project website) using JAX and Flax

Clockwork VAEs in JAX/Flax Implementation of experiments in the paper Clockwork Variational Autoencoders (project website) using JAX and Flax, ported

Julius Kunze 26 Oct 05, 2022
Text and code for the forthcoming second edition of Think Bayes, by Allen Downey.

Think Bayes 2 by Allen B. Downey The HTML version of this book is here. Think Bayes is an introduction to Bayesian statistics using computational meth

Allen Downey 1.5k Jan 08, 2023
Pyeventbus: a publish/subscribe event bus

pyeventbus pyeventbus is a publish/subscribe event bus for Python 2.7. simplifies the communication between python classes decouples event senders and

15 Apr 21, 2022
Machine Learning Models were applied to predict the mass of the brain based on gender, age ranges, and head size.

Brain Weight in Humans Variations of head sizes and brain weights in humans Kaggle dataset obtained from this link by Anubhab Swain. Image obtained fr

Anne Livia 1 Feb 02, 2022